This study presents a comprehensive investigation of blood flow and heat transfer in a stenotic artery using semi-analytical modeling. The Akbari–Ganji Method (AGM) was employed to solve nonlinear governing equations with infinite boundary conditions. A penta hybrid nanofluid (PHNF) was introduced and compared with a ternary hybrid nanofluid (THNF), where results showed that PHNF generates lower velocity profiles due to higher effective viscosity but provides superior temperature distributions because of enhanced thermal conductivity and energy absorption. Parametric analysis revealed that the magnetic parameter (M) reduces velocity but increases temperature, while the Casson parameter (β) decreases velocity and elevates temperature. The curvature parameter (γ) improves velocity, while nanoparticle volume fraction (ϕ) enhances heat transfer. Furthermore, higher Eckert number (Ec) and shape factor (sf) were found to increase temperature. Optimization through the Taguchi method and Response Surface Methodology (RSM) identified ϕ and β as the most significant parameters influencing skin friction, with M having a secondary role and γ a negligible effect, while ϕ and sf were shown to dominate heat transfer enhancement. The integration of AGM with PHNF modeling offers a robust framework for predicting and optimizing hemodynamic and thermal responses in stenotic arteries, with potential applications in drug delivery, hyperthermia treatment, vascular flow regulation, and biomedical diagnostics.
Mahboobtosi et al. (Sun,) studied this question.